Future directions on integrated wildlife monitoring based on non-invasive approaches in Europe

The growing trend of emerging diseases at the wildlife-livestock-human interface underscores the need to establish integrated surveillance strategies within a One Health framework. In Europe, Integrated Wildlife Monitoring (IWM) tends to focus on specific pathogens, often with limited spatial and temporal scope. In this perspectives article, we address some of the most recent technological advances that could strengthen future IWM programs, with special emphasis on non-invasive approaches for monitoring wildlife populations and pathogen communities. We analyse the potential complementarity of different monitoring tools, such as camera traps, unmanned aerial vehicles, acoustic recording, and especially the detection of environmental nucleic acids (ENAD) using next-generation sequencing techniques, for the simultaneous characterization of pathogen and host communities. Despite the potential of molecular tools for large-scale monitoring, the lack of methodological standardization, the limited capacity to obtain quantitative information (e.g. population abundance or pathogen prevalence), and the difficulty of inferring the epidemiological significance of findings (e.g. whether molecular detection indicates viable pathogen) remain key challenges that limit their application. Finally, we argue that integrating these technologies with artificial intelligence (AI) represents a promising approach for managing large, heterogeneous datasets and developing proactive early warning systems. Moving toward the implementation of standardized and harmonized strategies that integrate ecological and epidemiological information should be a priority in European health surveillance frameworks. Strengthening coordination among surveillance systems by incorporating multi-source, AI-supported approaches will be key to improving early detection capacity and supporting evidence-based decision-making in addressing the global emergence of diseases.